The client is a large-scale manufacturing company producing industrial equipment and components. The company has a wide vendor base with complex logistics networks, and, therefore, requires better control over its supply chain operations.
The core objective was to monitor shipment progress and forecast inventory requirements, and get early alerts for potential issues. The client wanted a digital platform for real-time visibility into their supply chain for making more informed decisions.
The client’s supply chain data was highly fragmented across different departments and suppliers. The lack of a unified view led to frequent delays in shipment, overstocking of some materials, and stockouts of others. The client made reactive decisions rather than data-driven prescriptive decisions due to a lack of proper insights, which affected continuity and operational costs significantly.
The biggest challenge for the client was to consolidate data from diverse sources into a single source of truth. Other challenges include data discrepancies and delays in manual entries that led to issues related to accuracy in inventory and other data.
The client also faced difficulties in user access control and data segmentation. It was cumbersome for the client to ensure secure and role-based access for employees while maintaining the performance of the business system.
Our in-house team of experienced web developers made a Python-based web portal to unify the client’s supply chain data using features like-
We added predictive models to estimate future inventory requirements based on historical data and market trends.
Real-time alerts on shipment delays and shortages of stocks help the client proactively address supply chain disruptions.
We added tailored access levels for procurement teams, plant managers, and external vendors.
We created an interactive dashboard for monitoring shipments and viewing delay reports with vendor scorecards.
Our web solution improved the client’s operational control significantly, resulting in real-time supply chain visibility. More accurate demand forecasting reduced inventory holding costs by 18 percent and emergency purchases by 25 percent. The client was happy to get improved accountability and higher visibility across all service levels.
